A Personalized Diet and Workout Recommendation System Using Generative AI: Integrating Lang Chain and Indian Knowledge Systems

This study presents a comparative analysis of rule-based and generative AI-based diet and workout recommendation systems, highlighting their effectiveness in delivering personalized health guidance. The rule-based model relies on predefined logic and static conditions, whereas the generative system leverages OpenAI’s language models via Lang Chain to generate dynamic, context-aware recommendations based on user inputs. To augment this comparison with cultural richness and holistic understanding, aspects of Indian Knowledge Systems (IKS) specifically Ayurveda and indigenous fitness practices such as Yoga are brought in as a complementary model. Prakriti (constitution of the body), Ritucharya (seasonal adjustment), and food-mind typologies (Satvik, Rajasik, Tamasik) form a basis for culturally sensitive customization. The blending of IKS has the potential to improve both systems by infusing conventional health knowledge into contemporary AI-based recommendation systems, thus enhancing relevance, acceptability, and user satisfaction in multicultures.